Ronald P. Neilson

Toward a rule-based biome model

Current projections of the response of the biosphere to global climatic change indicate as much as 50% to 90% spatial displacement of extratropical biomes. The mechanism of spatial shift could be dominated by either 1) competitive displacement of northern biomes by southern biomes, or 2) drought-induced dieback of areas susceptible to change. The current suite of global biosphere models cannot distinguish between these two processes, thus determining the need for a mechanistically based biome model. The first steps have been taken towards the development of a rule-based, mechanistic model of regional biomes at a continental scale. The computer model is based on a suite of empirically generated conceptual models of biome distribution. With a few exceptions the conceptual models are based on the regional water balance and the potential supply of water to vegetation from two different soil layers, surface for grasses and deep for woody vegetation. The seasonality of precipitation largely determines the amount and timing of recharge of each of these soil layers and thus, the potential mixture of vegetative life-forms that could be supported under a specific climate. The current configuration of rules accounts for the potential natural vegetation at about 94% of 1211 climate stations over the conterminous U.S. Increased temperatures, due to global warming, would 1) reduce the supply of soil moisture over much of the U.S. by reducing the volume of snow and increasing winter runoff, and 2) increase the potential evapotranspiration (PET). These processes combined would likely produce widespread drought-induced dieback in the nation’s biomes. The model is in an early stage of development and will require several enhancements, including explicit simulation of PET, extension to boreal and tropical biomes, a shift from steady-state to transient dynamics, and validation on other continents.

Vegetation redistribution: A possible biosphere source of CO2 during climatic change

A new biogeographic model, MAPSS, predicts changes in vegetation leaf area index (LAI), site water balance and runoff, as well as changes in Biome boundaries. Potential scenarios of equilibrium vegetation redistribution under 2 x CO2 climate from five different General Circulation Models (GCMs) are presented. In general, large spatial shifts in temperate and boreal vegetation are predicted under the different scenarios; while, tropical vegetation boundaries are predicted (with one exception) to experience minor distribution contractions. Maps of predicted changes in forest LAI imply drought-induced losses of biomass over most forested regions, even in the tropics. Regional patterns of forest decline and dieback are surprisingly consistent among the five GCM scenarios, given the general lack of consistency in predicted changes in regional precipitation patterns. Two factors contribute to the consistency among the GCMs of the regional ecological impacts of climatic change: 1) regional, temperature-induced increases in potential evapotranspiration (PET) tend to more than offset regional increases in precipitation; and, 2) the unchanging background interplay between the general circulation and the continental margins and mountain ranges produces a fairly stable pattern of regionally specific sensitivity to climatic change. Two areas exhibiting among the greatest sensitivity to drought-induced forest decline are eastern North America and eastern Europe to western Russia. Drought-induced vegetation decline (losses of LAI), predicted under all GCM scenarios, will release CO2 to the atmosphere; while, expansion of forests at high latitudes will sequester CO2. The imbalance in these two rate processes could produce a large, transient pulse of CO2 to the atmosphere.

The Transient Response of Vegetation to Climate Change: A Potential Source of CO2 to the Atmosphere

Global climate change as currently simulated could result in the broad-scale redistribution of vegetation across the planet. Vegetation change could occur through drought-induced dieback and fire. The direct combustion of vegetation and the decay of dead biomass could result in a release of carbon from the biosphere to the atmosphere over a 50- to 150-year time frame. A simple model that tracks dieback and regrowth of extra-tropical forests is used to estimate the possible magnitude of this carbon pulse to the atmosphere. Depending on the climate scenario and model assumptions, the carbon pulse could range from 0 to 3 Gt of C yr−1. The wide range of pulse estimates is a function of uncertainties in the rate of future vegetation change and in the values of key model parameters.

Biotic regionalization and climatic controls in western North America

New methods of weather analysis accompanied by microhabitat ‘bioassays’ have been applied in several case studies to demonstrate effects of atmospheric processes on patterns of community composition and structure and potential species evolution. Average spatial and seasonal airmass dynamics which determine regional and elevational patterns of relative microhabitat favorability, were found to vary between a recent global warming trend (ca 1900 to 1940) and the subsequent global cooling trend (ca 1940 to 1970). These apparently systematic spatial and temporal shifts in weather were related to plant establishment patterns and community composition and structure. The proposed causal mechanisms function, in part, through regional shifts in microhabitat size. These effects are similar to larger scale, longer term shifts deduced from the late Quaternary fossil record. By modifying the spatial approach, month-to-month and year-to-year variability of weather has been examined for the last 130 years at individual points in southwestern North America. Three climatic regimes (the end of the Little Ice Age, the recent warming trend and the recent cooling trend) exhibited distinct year-to-year patterns of weather that can be related to the establishment of different kinds of plants (e.g., C4 grasses versus C3 shrubs). Oscillations between different temporal climatic regimes appear to promote the episodic establishment of different life forms, but not necessarily their local extinction. The two methods of weather analysis have been combined in a regional assessment of climatic controls of different biomes in space and time with a primary focus on the Chihuahuan desert. Natural ecotones between the Chihuahuan desert and neighboring biomes are clearly related to large scale airmass dynamics associated with seasonal oscillations in jetstream position. The weather patterns controlling ecotonal positions result from seasonal topographic influences on the general circulation of the atmosphere. The apparent stability of these patterns allows causal hypotheses of biogeographic dynamics and the evolution of physiological traits and life history characteristics.

Evaluation of continental carbon cycle simulations with North American flux tower observations

Terrestrial biosphere models can help identify physical processes that control carbon dynamics, including land-atmosphere CO2 fluxes, and have great potential to predict the terrestrial ecosystem response to changing climate. The skill of models that provide continental-scale carbon flux estimates, however, remains largely untested. This paper evaluates the performance of continental-scale flux estimates from 17 models against observations from 36 North American flux towers. Fluxes extracted from regional model simulations were compared with co-located flux tower observations at monthly and annual time increments. Site-level model simulations were used to help interpret sources of the mismatch between the regional simulations and site-based observations. On average, the regional model runs overestimated the annual gross primary productivity (5%) and total respiration (15%), and they significantly underestimated the annual net carbon uptake (64%) during the time period 2000- 2005. Comparison with site-level simulations implicated choices specific to regional model simulations as contributors to the gross flux biases, but not the net carbon uptake bias. The models performed the best at simulating carbon exchange at deciduous broadleaf sites, likely because a number of models used prescribed phenology to simulate seasonal fluxes. The models did not perform as well for crop, grass, and evergreen sites. The regional models matched the observations most closely in terms of seasonal correlation and seasonal magnitude of variation, but they have very little skill at interannual correlation and minimal skill at interannual magnitude of variability. The comparison of site vs. regional-level model runs demonstrated that (1) the interannual correlation is higher for site-level model runs, but the skill remains low; and (2) the underestimation of year-to-year variability for all fluxes is an inherent weakness of the models. The best-performing regional models that did not use flux tower calibration were CLM-CN, CASA-GFEDv2, and SIB3.1. Two flux tower calibrated, empirical models, EC-MOD and MOD17þ, performed as well as the best process-based models. This suggests that (1) empirical, calibrated models can perform as well as complex, process-based models and (2) combining process- based model structure with relevant constraining data could significantly improve model performance.

Climatic Constraints and Issues of Scale Controlling Regional Biomes

The prospect of climatic change threatens to cause large changes in regional biomes. These effects could be in the form of qualitative changes within biomes, as well as spatial changes in the boundaries of biomes. The boundaries, or ecotones, between biomes have been suggested as potentially sensitive areas to climatic change and therefore useful for monitoring change. Regional gradients of vegetation habitat size and variability are explored for their utility in detecting ecotone location and movement as driven by climatic change. Maximal habitat variability, as indicated by differential survivorship of plants, occurs at the ecotones or transitions between biomes. The principles developed for the analysis of abrupt changes in spatial habitat patterns (ecotones) will also be considered for the analysis and detection of potentially abrupt physiognomic changes through time (thresholds) over large regions. Extensive regional changes in habitat variability could occur rapidly, indicating an impending ‘ecotone’ in time (threshold) over much of the region. Rapid, regional changes could produce significant negative impacts on biological diversity. The two types of change, boundary shifts of regions and physiognomic shifts within regions, are potentially independent and may require different monitoring strategies to detect impending change.

Modeling Potential Equilibrium States of Vegetation and Terrestrial Water Cycle of Mesoamerica under Climate Change Scenarios

The likelihood and magnitude of the impacts of climate change on potential vegetation and the water cycle in Mesoamerica is evaluated. Mesoamerica is a global biodiversity hotspot with highly diverse topographic and climatic conditions and is among the tropical regions with the highest expected changes in precipitation and temperature under future climate scenarios. The biogeographic soil-vegetation-atmosphere model Mapped Atmosphere Plant Soil System (MAPSS) was used for simulating the integrated changes in leaf area index (LAI), vegetation types (grass, shrubs, and trees), evapotranspiration, and runoff at the end of the twenty-first century. Uncertainty was estimated as the likelihood of changes in vegetation and water cycle under three ensembles of model runs, one for each of the groups of greenhouse gas emission scenarios (low, intermediate, and high emissions), for a total of 136 runs generated with 23 general circulation models (GCMs). LAI is likely to decrease over 77%-89% of the region, depending on climate scenario groups, showing that potential vegetation will likely shift from humid to dry types. Accounting for potential effects of CO2 on water use efficiency significantly decreased impacts on LAI. Runoff will decrease across the region even in areas where precipitation increases (even under increased water use efficiency), as temperature change will increase evapotranspiration. Higher emission scenarios show lower uncertainty (higher likelihood) in modeled impacts. Although the projection spread is high for future precipitation, the impacts of climate change on vegetation and water cycle are predicted with relatively low uncertainty.

Regional and Local Vegetation Patterns: The Responses of Vegetation Diversity to Subcontinental Air Masses

The prospect of global change, fostered by human impacts on the global climate and by extensive alteration of the natural landscape, has raised concerns over the fate of the earth’s natural biological diversity. Unfortunately, a definitive theory on the causes of biological diversity has been elusive. The absence of such a theory makes it difficult to project the consequences of global change on biodiversity. The ideal theory of biodiversity must, at least, be able to explain the spatial patterns of biodiversity and their changes through time. Our intent, in this chapter, is to explore some of the spatial patterns of biodiversity and to propose a few mechanisms that appear to account for much of this pattern. We are particularly attentive to the potential climatic drivers of spatial patterns of biodiversity.

A new model to simulate climate‐change impacts on forest succession for local land management

We developed a new climate-sensitive vegetation state-and-transition simulation model (CV-STSM) to simulate future vegetation at a fine spatial grain commensurate with the scales of human land-use decisions, and under the joint influences of changing climate, site productivity, and disturbance. CV-STSM integrates outputs from four different modeling systems. Successional changes in tree species composition and stand structure were represented as transition probabilities and organized into a state-and-transition simulation model. States were characterized based on assessments of both current vegetation and of projected future vegetation from a dynamic global vegetation model (DGVM). State definitions included sufficient detail to support the integration of CV-STSM with an agent-based model of land-use decisions and a mechanistic model of fire behavior and spread. Transition probabilities were parameterized using output from a stand biometric model run across a wide range of site productivities. Biogeographic and biogeochemical projections from the DGVM were used to adjust the transition probabilities to account for the impacts of climate change on site productivity and potential vegetation type. We conducted experimental simulations in the Willamette Valley, Oregon, USA. Our simulation landscape incorporated detailed new assessments of critically imperiled Oregon white oak (Quercus garryana) savanna and prairie habitats among the suite of existing and future vegetation types. The experimental design fully crossed four future climate scenarios with three disturbance scenarios. CV-STSM showed strong interactions between climate and disturbance scenarios. All disturbance scenarios increased the abundance of oak savanna habitat, but an interaction between the most intense disturbance and climate-change scenarios also increased the abundance of subtropical tree species. Even so, subtropical tree species were far less abundant at the end of simulations in CV-STSM than in the dynamic global vegetation model simulations. Our results indicate that dynamic global vegetation models may overestimate future rates of vegetation change, especially in the absence of stand-replacing disturbances. Modeling tools such as CV-STSM that simulate rates and direction of vegetation change affected by interactions and feedbacks between climate and land-use change can help policy makers, land managers, and society as a whole develop effective plans to adapt to rapidly changing climate.

Terrestrial Ecosystem Changes

Models are used to estimate potential physical and biological impacts, efficient adaptations, and residual damages from climate change. The contributors cover a broad array of climate change impacts on affected market sectors (including water supply, agriculture, coastal resources, timber, and energy demand) as well as ecosystems and biodiversity. An integrated hydrologic-agriculture model is developed to explore how the region would adapt to changes in water flows. Interactions between climate impacts and population and economic growth, urbanization, and technological change are also explored. For example, the study examines how both climate change and projected land development affect the region’s terrestrial ecosystems and biodiversity.